Post by Siemens EDA (Siemens Digital Industries Software)

The semiconductor industry isn’t short on data, but it’s struggling to make that data truly useful.   EDA tools generate massive amounts of information across every stage of design, but much of it was never structured for AI to fully take advantage of. As a result, valuable insights often remain buried, and engineers spend significant time navigating, interpreting, and reusing data across workflows.    What’s changing now is how that data is being treated. There’s a growing focus on making it more structured, connected, and context-aware, so it can support AI-driven decision making. Combined with agent-based workflows that learn from previous runs, and frameworks like MCP that better connect tools and systems, this creates a more continuous and intelligent design process. Instead of starting from scratch each time, teams can build on prior knowledge, reduce iteration cycles, and move faster with greater confidence.